Hiori Kino

4.7k total citations · 1 hit paper
91 papers, 3.7k citations indexed

About

Hiori Kino is a scholar working on Materials Chemistry, Electronic, Optical and Magnetic Materials and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Hiori Kino has authored 91 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Materials Chemistry, 33 papers in Electronic, Optical and Magnetic Materials and 26 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Hiori Kino's work include Organic and Molecular Conductors Research (19 papers), Machine Learning in Materials Science (18 papers) and Magnetism in coordination complexes (16 papers). Hiori Kino is often cited by papers focused on Organic and Molecular Conductors Research (19 papers), Machine Learning in Materials Science (18 papers) and Magnetism in coordination complexes (16 papers). Hiori Kino collaborates with scholars based in Japan, France and South Korea. Hiori Kino's co-authors include Taisuke Ozaki, Hidetoshi Fukuyama, Takashi Miyake, Hiroshi Kontani, Kengo Nishio, Tsuyoshi Miyazaki, Kiyoyuki Terakura, Takahisa Ohno, Jun Nara and Hisashi Kondo and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and SHILAP Revista de lepidopterología.

In The Last Decade

Hiori Kino

89 papers receiving 3.6k citations

Hit Papers

Numerical atomic basis orbitals from H to Kr 2004 2026 2011 2018 2004 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hiori Kino Japan 26 1.8k 1.4k 1.2k 1.2k 877 91 3.7k
Takashi Miyake Japan 40 2.3k 1.3× 2.2k 1.6× 1.8k 1.5× 518 0.4× 2.0k 2.3× 140 5.1k
L. Bahmad Morocco 42 3.1k 1.7× 2.1k 1.5× 1.5k 1.3× 1.4k 1.2× 2.0k 2.2× 300 5.1k
A. Jabar Morocco 35 2.0k 1.1× 1.6k 1.1× 1.3k 1.1× 585 0.5× 1.8k 2.1× 243 3.7k
Manish Jain India 34 3.0k 1.6× 702 0.5× 1.5k 1.3× 2.0k 1.7× 512 0.6× 149 4.6k
Jian Shen China 34 2.0k 1.1× 1.8k 1.3× 1.4k 1.2× 956 0.8× 1.1k 1.3× 145 3.8k
Taisuke Ozaki Japan 30 4.7k 2.5× 995 0.7× 2.8k 2.4× 1.8k 1.6× 883 1.0× 127 6.4k
Michiel J. van Setten Belgium 27 2.5k 1.4× 420 0.3× 1.4k 1.2× 1.2k 1.1× 632 0.7× 70 3.8k
Dapeng Yu China 33 2.6k 1.4× 632 0.4× 1.2k 1.0× 1.4k 1.2× 434 0.5× 156 4.0k
B. Movaghar Germany 35 1.8k 1.0× 764 0.5× 1.5k 1.3× 2.0k 1.7× 498 0.6× 134 4.2k
Maximilian Amsler Switzerland 28 2.2k 1.2× 452 0.3× 526 0.4× 525 0.5× 340 0.4× 61 2.8k

Countries citing papers authored by Hiori Kino

Since Specialization
Citations

This map shows the geographic impact of Hiori Kino's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hiori Kino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hiori Kino more than expected).

Fields of papers citing papers by Hiori Kino

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hiori Kino. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hiori Kino. The network helps show where Hiori Kino may publish in the future.

Co-authorship network of co-authors of Hiori Kino

This figure shows the co-authorship network connecting the top 25 collaborators of Hiori Kino. A scholar is included among the top collaborators of Hiori Kino based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hiori Kino. Hiori Kino is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tran, Truyen, Hiori Kino, Nozomu Ishiguro, et al.. (2025). PID3Net: a deep learning approach for single-shot coherent X-ray diffraction imaging of dynamic phenomena. npj Computational Materials. 11(1).
2.
Huan, Tran Doan, Hieu‐Chi Dam, Christopher Künneth, Vu Ngoc Tuoc, & Hiori Kino. (2024). Superconductor Discovery in the Emerging Paradigm of Materials Informatics. Chemistry of Materials. 36(22). 10939–10966. 2 indexed citations
3.
Kino, Hiori, Yasunobu Ando, Takashi Miyake, et al.. (2023). Evidence-based data mining method to reveal similarities between materials based on physical mechanisms. Journal of Applied Physics. 133(5). 1 indexed citations
4.
Tran, Truyen, Tran Doan Huan, Hiori Kino, et al.. (2023). Towards understanding structure–property relations in materials with interpretable deep learning. npj Computational Materials. 9(1). 23 indexed citations
5.
Fukushima, Tetsuya, H. Akai, Toyohiro Chikyow, & Hiori Kino. (2022). Automatic exhaustive calculations of large material space by Korringa-Kohn-Rostoker coherent potential approximation method applied to equiatomic quaternary high entropy alloys. Physical Review Materials. 6(2). 10 indexed citations
6.
Yamashita, Tomoki, Hiori Kino, Koji Tsuda, Takashi Miyake, & Tamio Oguchi. (2022). Hybrid algorithm of Bayesian optimization and evolutionary algorithm in crystal structure prediction. SHILAP Revista de lepidopterología. 2(1). 67–74. 4 indexed citations
7.
Kino, Hiori, et al.. (2021). Characterization of descriptors in machine learning for data-based sputtering yield prediction. Physics of Plasmas. 28(1). 21 indexed citations
8.
Nagata, Takahiro, Toyohiro Chikyow, Hiori Kino, et al.. (2021). Evidence-based recommender system for high-entropy alloys. Nature Computational Science. 1(7). 470–478. 23 indexed citations
9.
Kino, Hiori. (2020). Prediction of plasma etching yields by machine learning to reveal the complexity of underlying physics. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
10.
Kino, Hiori, Kohji Nakamura, Koji Hukushima, Takashi Miyake, & Hieu‐Chi Dam. (2020). Maximum Separated Distribution with High Interpretability Found Using an Exhaustive Search Method —Application to Magnetocrystalline Anisotropy of Fe/Co Films—. Journal of the Physical Society of Japan. 89(6). 64802–64802. 2 indexed citations
12.
13.
Kino, Hiori, et al.. (2019). Learning Materials Properties from Orbital Interactions. Journal of Physics Conference Series. 1290(1). 12012–12012. 1 indexed citations
14.
Ishibashi, Shoji, Akira Uedono, Hiori Kino, Takashi Miyake, & Kiyoyuki Terakura. (2019). Computational study of positron annihilation parameters for cation mono-vacancies and vacancy complexes in nitride semiconductor alloys. Journal of Physics Condensed Matter. 31(47). 475401–475401. 17 indexed citations
15.
Dam, Hieu‐Chi, et al.. (2018). Important Descriptors and Descriptor Groups of Curie Temperatures of Rare-earth Transition-metal Binary Alloys. Journal of the Physical Society of Japan. 87(11). 113801–113801. 23 indexed citations
16.
Kino, Hiori, Kiyoyuki Terakura, Takashi Miyake, et al.. (2017). Machine learning reveals orbital interaction in materials. Science and Technology of Advanced Materials. 18(1). 756–765. 97 indexed citations
17.
Miyake, Takashi, et al.. (2014). NdFe 12 ,NdFe 11 Ti,およびNdFe 11 TiNにおける磁気結晶異方性と磁化に関する第一原理研究. Journal of the Physical Society of Japan. 83(4). 1–43702. 1 indexed citations
18.
Kino, Hiori & Tsuyoshi Miyazaki. (2009). First-Principles Study of the Tilted Dirac Cone in α-(BEDT-TTF)2I3at Hydrostatic Pressures. Journal of the Physical Society of Japan. 78(10). 105001–105001. 3 indexed citations
19.
Kino, Hiori, F. Aryasetiawan, Takashi Miyake, & Kiyoyuki Terakura. (2002). Abnormal Quasiparticle Shifts of CaB_6. APS March Meeting Abstracts.
20.
Mori, Michiyasu, Kenji Yonemitsu, & Hiori Kino. (1999). Possible magnetic phases in two-band systems with different dimensionality. Synthetic Metals. 103(1-3). 1883–1884. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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